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This study guide provides a collection of questions and answers related to data management foundations, covering key concepts like entities, attributes, relationships, constraints, and database models. It offers a basic understanding of data management principles and terminology, suitable for introductory learning.
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o Represents a particular type of object and is distinguishable o Each occurrence is unique and distinct EXAMPLE: John Smith, John Strickland. Each customer is unique and distinct"
o Equivalent to fields in a file system EXAMPLE: Customers last name, First name, Phone number or Address"
o Are bidirectional"
o Helps ensure data integrity o Expressed in the form of rules EXAMPLE: 6,000 and 350,000, GPA must be between 0.00 and 4.00 or Class must have one and only one teacher"
procedure, or principle within a organization"
the model · Verb (active or passive) that associates the nouns will translate into a relationship among the entities"
· Two-dimensional structure composed of intersecting rows and columns o Provides a minimum level of control redundancy to eliminate most of the word unseen commonly found in file systems"
functions provided by Hierarchical and Network DBMS o Advantage is its ability to hide complexities of relational model from the user o Manages all physical details, while user sees relational database as a collection of tables"
Diagram (ERD) which uses graphical representations to model database components"
one record in the second table And o A single record in the second table is related to only one record in the first table"
one or more records in the second table But o a single record in the second table can be related to only one record in the first table Example: Each painting was created by one and only one painter Each painter could have created many paintings"
to one or more records in the second table And o A single record in the second table can be related to one or more records in the first table Ex. An employee may learn many job skills, and each skill can be learned by many employees."
o Implies familiarity awareness and understanding of Information o Key Characteristic is that New Knowledge can be derived from Old Knowledge"
storage, and retrieval of data"
o Receives all application requests and translates them into complex operations"
-improves data security
· Supports the storage and management of Semi Structured XML data"
database model o Designed to handle unprecedented volumes, variety types, structure of data IOT support the velocity of data operations required in businesses"
management and generates accurate invaluable information"
Difficulty of getting quick answers, Complex system administration, Lack of security and limited data sharing, Extensive programming"
schema, affects database access, requiring changes to all access programs file changes"
database schema DOES NOT affect database access"
manipulation are dependent on physical data storage characteristics affecting access to the data"
manipulation IS NOT dependent on physical data storage characteristics and DOES NOT affect access the data"
(scattered in different locations "Islands of Information")"
· Data that is verifiable - will always yield consistent results"
o Develops when not all required changes in the redundant data or made successfully o Types of data anomalies include Update, Insertion or Deletion"
removes structural and data dependence from the system"
database Performance Tuning o Performance tuning allows for the database to access data fast and efficiently"
a specific model for a determined problem domain"
with a well-defined scope and boundaries that will be systematically addressed"
environment Represents data structures, characteristics, relations, constraint, transformations, in other constructs with the purpose of supporting a specific problem domain o Implementation ready data models should contain: · Description of the data structure that will store end user data · A set of enforceable rules to guarantee integrity · A data manipulation methodology to support data transformations"
· Facilitate interaction among the designer, the applications programmer, and the end user"
o Velocity- The speed with which data grows. The need to process data quickly to generate information and insight o Variety- The data being collected comes in multiple different data formats"
web/ sensor-generated data and derive business insight from it, while simultaneously providing high performance and scalability at a reasonable cost"
· Specifically, that an entity has been involved in an action that involves another · Includes any intersection data that describes the relationship in its information"
rather than physically. o Logical view facilitated by relationships based on logical construct call a relation"
attribute's set of possible values."
rows in a table o Composed of an Index Key and Set of Pointers o Used to retrieve data more efficiently o Used by DBMS to retrieve data ordered by a specific attribute or attributes"
associated with another related entity occurrence o Exists if an entity has a mandatory foreign key attribute that cannot be null"
entities · Referred to as a Strong or Regular Entity"
of the same entity set"
minimize data redundancies, thereby reducing the likelihood of data anomalies o Properly designed 3NF structures also meet the requirements of fourth normal form (4NF)"
· No repeating groups in the table (each row/column intersection contains one and only one value, not a set of values) · Attributes are dependent on the primary key o All relational tables satisfy the 1NF requirements"
· No partial dependencies (no attribute is dependent on only a portion of the primary key)"
There are no transitive dependencies"
and processes used to capture, collect, integrate, store, and analyze data with the purpose of generating and presenting information to support business decision making"
relationships and their types"
predictions of future values and events"
area · Can be structured or unstructured · Data is tagged with metadata, source systems is identified, time stamped, and other important metadata · Requires executing programs to: o Purge/Expand existing staging tables or locations o Extract data from source systems o Load Staging Area with data/metadata"
o Merging data o Sorting data o Converting data o Aggregating data o Tagging data o Key data o Deriving columns · Data that does not conform to transformation processing is sent to rework tables"
on a disk · Allows for faster data look up without the use of an index file"
better understand."
o Key to good decision making and business survival is accurate, relevant, and timely information"